支持10w級調(diào)度！新鮮出爐的SnailJob性能壓測報告
當(dāng)下企業(yè)業(yè)務(wù)系統(tǒng)復(fù)雜，任務(wù)調(diào)度、任務(wù)失敗重試、安全控制、監(jiān)控告警等需求層出不窮，許多傳統(tǒng)方案都面臨接入復(fù)雜、擴展成本高、失敗重試機制單一等痛點。
當(dāng)下企業(yè)業(yè)務(wù)系統(tǒng)復(fù)雜，任務(wù)調(diào)度、任務(wù)失敗重試、安全控制、監(jiān)控告警等需求層出不窮，許多傳統(tǒng)方案都面臨接入復(fù)雜、擴展成本高、失敗重試機制單一等痛點。
SnailJob的誕生正是為了解決這些難題。
平臺概述
SnailJob 是一個專注于分布式任務(wù)調(diào)度與重試的平臺，采用分區(qū)分桶架構(gòu)具備極高的伸縮性和容錯性，無需依賴外部中間件即可實現(xiàn)秒級調(diào)度和復(fù)雜重試策略，同時擁有現(xiàn)代化 UI 和完善的權(quán)限與告警機制。
SnailJob 性能壓測報告
- 報告日期： 2025-08-25
- 版本: 1.7.2
- 提供者: rpei
測試目標(biāo)
本次壓測的目標(biāo)是驗證 單個 SnailJob 服務(wù)節(jié)點在穩(wěn)定條件下可支持的最大定時任務(wù)數(shù)量，并評估系統(tǒng)在高并發(fā)任務(wù)調(diào)度下的整體性能表現(xiàn)。
測試環(huán)境
?? 數(shù)據(jù)庫
- 類型： 阿里云 RDS MySQL 8.0
- 實例規(guī)格： mysql.n2.xlarge.1（8 vCPU，16 GB 內(nèi)存）
- 存儲： 100 GB，InnoDB 引擎
- 版本： MySQL_InnoDB_8.0_Default
?? 應(yīng)用部署
- 服務(wù)器信息： 阿里云 ECS g6.4xlarge
- SnailJob Server： 單實例（4 vCPU，8 GB 內(nèi)存）
- SnailJob Client： 16 個實例（每個 1 vCPU，1 GB 內(nèi)存）
服務(wù)端配置
pekko配置(snail-job-server-starter/src/main/resources/snailjob.conf)
pekko {
actor {
common-log-dispatcher {
type = "Dispatcher"
executor = "thread-pool-executor"
thread-pool-executor {
core-pool-size-min = 16
core-pool-size-factor = 1.0
core-pool-size-max = 256
}
throughput = 10
}
common-scan-task-dispatcher {
type = "Dispatcher"
executor = "thread-pool-executor"
thread-pool-executor {
core-pool-size-min = 64
core-pool-size-factor = 1.0
core-pool-size-max = 256
}
throughput = 10
}
netty-receive-request-dispatcher {
type = "Dispatcher"
executor = "thread-pool-executor"
thread-pool-executor {
core-pool-size-min = 128
core-pool-size-factor = 1.0
core-pool-size-max = 256
}
throughput = 10
}
retry-task-executor-dispatcher {
type = "Dispatcher"
executor = "thread-pool-executor"
thread-pool-executor {
core-pool-size-min = 32
core-pool-size-factor = 1.0
core-pool-size-max = 256
}
throughput = 10
}
retry-task-executor-call-client-dispatcher {
type = "Dispatcher"
executor = "thread-pool-executor"
thread-pool-executor {
core-pool-size-min = 32
core-pool-size-factor = 1.0
core-pool-size-max = 256
}
throughput = 10
}
retry-task-executor-result-dispatcher {
type = "Dispatcher"
executor = "thread-pool-executor"
thread-pool-executor {
core-pool-size-min = 32
core-pool-size-factor = 1.0
core-pool-size-max = 256
}
throughput = 10
}
job-task-prepare-dispatcher {
type = "Dispatcher"
executor = "thread-pool-executor"
thread-pool-executor {
core-pool-size-min = 128
core-pool-size-factor = 1.0
core-pool-size-max = 256
}
throughput = 10
}
job-task-executor-dispatcher {
type = "Dispatcher"
executor = "thread-pool-executor"
thread-pool-executor {
core-pool-size-min = 160
core-pool-size-factor = 1.0
core-pool-size-max = 256
}
throughput = 10
}
job-task-executor-call-client-dispatcher {
type = "Dispatcher"
executor = "thread-pool-executor"
thread-pool-executor {
core-pool-size-min = 160
core-pool-size-factor = 1.0
core-pool-size-max = 256
}
throughput = 10
}
job-task-executor-result-dispatcher {
type = "Dispatcher"
executor = "thread-pool-executor"
thread-pool-executor {
core-pool-size-min = 160
core-pool-size-factor = 1.0
core-pool-size-max = 256
}
throughput = 10
}
workflow-task-prepare-dispatcher {
type = "Dispatcher"
executor = "thread-pool-executor"
thread-pool-executor {
core-pool-size-min = 4
core-pool-size-factor = 1.0
core-pool-size-max = 256
}
throughput = 10
}
workflow-task-executor-dispatcher {
type = "Dispatcher"
executor = "thread-pool-executor"
thread-pool-executor {
core-pool-size-min = 4
core-pool-size-factor = 1.0
core-pool-size-max = 512
}
throughput = 10
}
}
}系統(tǒng)配置文件(snail-job-server-starter/src/main/resources/application.yml)
server:
port: 8080
servlet:
context-path: /snail-job
spring:
main:
banner-mode: off
profiles:
active: dev
datasource:
name: snail_job
## mysql
driver-class-name: com.mysql.cj.jdbc.Driver
url: jdbc:mysql://ex-snailjob-mysql-svc:3306/snail_job?useSSL=false&characterEncoding=utf8&useUnicode=true
username: root
password: Ab1234567
type: com.zaxxer.hikari.HikariDataSource
hikari:
connection-timeout: 30000
minimum-idle: 16
maximum-pool-size: 256
auto-commit: true
idle-timeout: 30000
pool-name: snail_job
max-lifetime: 1800000
web:
resources:
static-locations: classpath:admin/
mybatis-plus:
typeAliasesPackage: com.aizuda.snailjob.template.datasource.persistence.po
global-config:
db-config:
where-strategy: NOT_EMPTY
capital-mode: false
logic-delete-value: 1
logic-not-delete-value: 0
configuration:
map-underscore-to-camel-case: true
cache-enabled: true
logging:
config: /usr/snailjob/config/logback.xml
snail-job:
retry-pull-page-size: 2000 # 拉取重試數(shù)據(jù)的每批次的大小
job-pull-page-size: 2000 # 拉取重試數(shù)據(jù)的每批次的大小
server-port: 17888 # 服務(wù)器端口
log-storage: 7 # 日志保存時間(單位: day)
rpc-type: grpc
summary-day: 0
server-rpc:
keep-alive-time: 45s # 心跳間隔45秒
keep-alive-timeout: 15s # 心跳超時15秒
permit-keep-alive-time: 30s # 允許心跳間隔30秒
dispatcher-tp: # 調(diào)度線程池配置
core-pool-size: 100
maximum-pool-size: 100
client-rpc:
keep-alive-time: 45s # 心跳間隔45秒
keep-alive-timeout: 15s # 心跳超時15秒
client-tp: # 客戶端線程池配置
core-pool-size: 100
maximum-pool-size: 100測試場景
- 每個定時任務(wù)的執(zhí)行周期：60 秒
- 單個任務(wù)平均執(zhí)行耗時：200 毫秒
- 測試目標(biāo)：測量單節(jié)點 SnailJob Server 可穩(wěn)定調(diào)度的任務(wù)數(shù)量
測試結(jié)果
在單節(jié)點（4C/8G）環(huán)境下，SnailJob Server 能夠穩(wěn)定承載 30,000 個定時任務(wù)，并保證任務(wù)在每 60 秒 內(nèi)按時執(zhí)行。此時數(shù)據(jù)庫負(fù)載率僅 20%，表明系統(tǒng)具備良好的可擴展性。通過水平擴展服務(wù)端節(jié)點，理論上可輕松支持 100,000+ 任務(wù)調(diào)度，滿足絕大多數(shù)企業(yè)的業(yè)務(wù)場景。 同時，SnailJob Pro 版本引入 Redis 緩存改造與日志剝離（基于 Mongo 存儲），進一步提升了系統(tǒng)的調(diào)度能力與穩(wěn)定性。
資源消耗情況(受公司保密限制，截圖無法公開，這里僅分享壓測的結(jié)果數(shù)據(jù))
指標(biāo) | 數(shù)據(jù) |
SnailJob服務(wù)端CPU使用率 | 均值：71% 峰值：82% |
SnailJob服務(wù)端內(nèi)存 | 約32% |
數(shù)據(jù)庫實例IOPS使用率 | 采樣間隔5秒峰值：40% |
數(shù)據(jù)庫實例CPU使用率 | 約20% |
數(shù)據(jù)庫實例內(nèi)存使用率 | 約55% |
總結(jié)
SnailJob 的性能瓶頸主要來源于 數(shù)據(jù)庫存儲。由于調(diào)度過程中存在大量任務(wù)批次與日志寫入操作，對數(shù)據(jù)庫 IOPS 會產(chǎn)生較大壓力。因此在部署 SnailJob 時，建議：
- 數(shù)據(jù)庫獨立部署，避免與其他業(yè)務(wù)服務(wù)共享實例；
- 優(yōu)先選擇高性能磁盤，以提升寫入效率；
- 開啟異步寫盤，進一步降低數(shù)據(jù)庫寫入延遲。
責(zé)任編輯：武曉燕
來源：
程序員wayn
